XMPPwocky

> IGN has accused the game developer for being sexist (based on some poorly translated social media posts) and gave it a low score before properly playing/testing it.

What score did they give it? Because I just checked and they seem to have awarded it an 8 out of 10. I don't follow game reviews, but surely review inflation hasn't gotten so bad that people are on some sort of anti-"woke" bent over an 8 out of 10?

I figured "well maybe they changed it after publication, those sneaky skags", so looked at the ol' Wayback Machine capture for Aug 16th, four days before launch, when the review embargo lifted: https://web.archive.org/web/20240816141422/https://www.ign.c...

8/10 there too- "Despite some frustrating technical issues, Black Myth: Wukong is a great action game with fantastic combat, exciting bosses, tantalizing secrets, and a beautiful world.". Really a horrible thing these journalists have done, ripping into the game like that.

Now, I did also find a report from IGN about 6 months ago that some people claim used "mistranslated quotes". But I don't speak Chinese, and the people online who I've found yelling at IGN about this appear to have used ChatGPT or Google Translate to translate things themselves! So- do you speak Chinese? If not, how do you know the claims of "mistranslation" are correct (again, for a thing that is not a review)?

Could you be more specific? What underclass (and why don't they matter?), and what segregation?

Experts in any field are generally not the ones communicating with, and making recommendations to, the public.

" by the same people that believe whatever they're told by anyone in authority, and then feel the urge to pass it on to others without critical thought."

respectfully, what the hell is this bit doing in your post?

In fact, humans will be running at relativistic speeds within this century, risking the total destruction of the Earth if they should ever trip over something and fall down.

Scary stuff. And it's not science fiction- it's based on real, observed trends and scaling laws. Seems impossible? Well, they said the four-minute mile was impossible, too.

Absolutely agree. When I was a kid, I took a MOOC (MITx 6.002x) because I was interested in EE. They said calculus was a prerequisite, which I didn't know yet, but I went ahead anyways; every time the course required calculus, I'd go read the relevant chapters in Strang's Calculus. Felt incredibly natural, and I ended up going through the rest of Strang just for fun- probably the best learning experience I've ever had, and I doubt I'd have ever done it without having the MOOC there to motivate the problem.

The existence of sentient AGIs would certainly have wide-ranging impacts on the law!

This case is not about sentient AGIs.

But bigger fixed-length instructions mean more I$ pressure, right?

What stops an attacker from uploading their own firmware that dumps out everything in OTP?

I have UI to enter a custom URL for search in Firefox for Android, with no extensions beyond Privacy Badger, Unhook, and uBlock Origin- interesting.

Are the activation functions truly different, or just different parameter values to one underlying function?

I see no sibling comment here even with showdead on, but I could buy that (there's a lot of papers and only so many parameters, after all- but you'd think GPT-4o's search stuff would help, maybe a little better prompting could get it to at least validate its results itself? then again, maybe the search stuff is basically RAG and only happens one at the start of the query, etc etc)

Regardless, yeah- I can definitely believe your point about corpus size. If I was doing, say, frontend dev with a stack that's been around a few years, or Linux kernel hacking as tptacek mentioned, I could plausibly imagine getting some value.

One thing I do do fairly often is binary reverse engineering work- there's definitely things an LLM could probably help with here (for things like decompilation, though, I wonder whether a more graph-based network could perform better than a token-to-token transformer - but you'd have to account for the massive data & pretrain advantage of an existing LLM).

So I've looked at things like Binary Ninja's Sidekick, but haven't found an opportunity to use them yet - confidentiality concerns rule out professional use, and when I reverse engineer stuff for fun ... I like doing it, I like solving the puzzle and slowly comprehending the logic of a mysterious binary! I'm not interested in using Sidekick off the clock for the same reason I like writing music and not just using Suno.

One opportunity that might come up for Sidekick, at least for me, is CTFs- no confidentiality concerns, time pressure and maybe prizes on the line. We'll see.

Every now and then, I'll actually sort of believe an article like this. Then I go and test the current models on things like semantic search.

For instance -

The Hough transform detects patterns with certain structure in images, e.g. circles or lines.

So I'm looking for academic research papers which apply the Hough transform to audio spectra, to recognize the harmonic structure of tonal audio and thus determine the fundamental pitch. (i.e. the Hough space would be a 1D space over fundamental frequency).

I've spent probably 90 minutes, over the several times I've read an optimistic post like this, asking various LLMs (mostly GPT-4o, though my early tests predate GPT-4o, and I've also tried Gemini and Claude), prompts along the lines of

> The Hough transform detects patterns with certain structure in images, e.g. circles or lines. > I'm looking for academic research papers (please link them or provide a DOI.org link at least) which apply the Hough transform to audio spectra, to identify the harmonic structure of audio and thus determine the fundamental pitch. > Make sure to provide only papers that actually exist. If you can't find anything particularly relevant, say so as a disclaimer & just provide the most relevant papers you can.

This is a reliable "fake paper generator", unfortunately - it'll just make up plausible garbage like

> Here are some academic papers related to applying the Hough transform to audio spectra for identifying harmonic structures and fundamental pitch:

> "An Audio Pitch Detection Algorithm Based on the Hough Transform" > Authors: Mark W. and John D. > Published In: IEEE Transactions on Audio, Speech, and Language Processing > DOI: 10.1109/TASL.2008.2000773 > Abstract: This paper proposes an audio pitch detection algorithm that utilizes the Hough transform to analyze the harmonic structure of audio spectra and determine the fundamental pitch.

This paper does not exist. Complete waste of my time. And again, this behavior persists over the >1 year period I've been trying this query.

And it's not just search-like tasks. I've tried asking for code and gotten stuff that's outright dangerous (try asking for code to do safe overflow-checked addition on int64_t in C- you have about an 80% chance of getting code that triggers UB in one way or another). I've asked for floating-point calling conventions on RISC-V for 32-bit vs 64-bit (would have been faster than going through the extension docs), and been told that RV64 has 64 floating-point registers (hey, it's got a 64 in the name!). I've asked if Satya Nadella ever had COVID-19 and been told- after GPT-4o "searched the web"- that he got it in March of 2023.

As far as I can tell, LLMs might conceivably be useful when all of the following conditions are true:

1. You don't really need the output to be good or correct, and 2. You don't have confidentiality concerns (sending data off to a cloud service), and, 3. You don't, yourself, want to learn anything or get hands-on - you want it done for you, and 4. You don't need the output to be in "your voice" (this is mostly for prose writing, for code this doesn't really matter); you're okay with the "LLM dialect" (it's crucial to delve!), and 5. The concerns about environmental impact and the ethics of the training set aren't a blocker for you.

For me, pretty much everything I do professionally fails condition number 1 and 2, and anything I do for fun fails number 3. And so, despite a fair bit of effort on my part trying to make these tools work for me, they just haven't found a place in my toolset- before I even get to 4 or 5. Local LLMs, if you're able to get a beefy enough GPU to run them at usable speed, solve 2 but make 1 even worse...

Thank you, this is very interesting!

Fascinating, thank you!

Do people go on dating sites to look at "hotties"? I've heard there are better websites to do that, many free of charge!

(Not a rhetorical question - as a queer person who's never used a dating site or app and who's been in a long-term relationship (now married) for almost 8 years now, I really do have no idea what people do on there.)

Is this (genes physically close together, but not contiguous, being affected by the same/related promoters) something commonly seen? I'd love to learn more about it if so!

For multimodal input, okay, I can see the argument. But since, as you said, training on generated data can be almost worse than useless, what's the point of generating it?

If I had these concerns as OpenAI, I'd be pushing hard to regulate and restrict generative image/video models, to push the end of the "low background data" era as far into the future as possible. i feel like the last thing I'd be doing is productizing those models myself!

> It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet.

Give it a few more years for more people to forget about how hard things like NFTs got pushed with the same sort of arguments- then this'll come off better.

How so? We've built huge amounts of infrastructure (parking being the obvious one) to explicitly enable people to have cars in city centers- stop doing that and my gut (scientific, I know!) says that'll get you most of the way there.

And for me on Firefox on Android, it renders as a blank space!

Did you reply to the right post?

You say "it's your responsibility to hold them accountable for their actions and to check at that level"- but all I see in the parent comments is people discussing politics. People saying "I think this law is bad" is a critical part of the exact democratic process you seem to hold in high regard. That's how you get a consensus among the electorate that can push representatives to oppose future surveillance legislation and repeal existing stuff.

(If you replied to the wrong comment, and meant to say this to somebody proposing overthrowing democracy or whatever, disregard my comment, obviously!)

How so? To my ears, "we need to accept significant degradations in the availability of electricity" is a deeply pessimistic statement.

Where can I read more about this?

Why do you think so?

Yeah- I started being "flexible" with contractions in casual online speech years ago as a joke, but now it's just sort of part of my "dialect". That and cursed multiple contractions; at least I'ven't'd any problems with accidentally using either of those in formal speech.

For board you didn't design, PCBite probes work, but can be fiddly especially when you have several've them in a small area.

I have a really good counter-argument to everything you've said, but I'm too scared to mention it- as you can see, my original post got downvoted

If you look further down in the paper, they mention the variables they adjusted for:

> [..] all models were adjusted for sex, birth year, area-level urbanicity, area-level morbidity, area-level educational level, area-level employ- ment rate, school class size, school’s ninth grade size, parental educational level, parental income, and parental mental health.

So a contaminant or other environmental factor that didn't correlate perfectly with those factors wouldn't be corrected for. How could it be, without knowing what it is?

> And the big one that's everywhere today that you can't talk about.

If you're not going to say what you actually think, why hint at it?